本研究主要基於財務的觀點,站在投資型購屋者的角度,運用折現現金流量法來評估地上權住宅之合理價值 (Fair Value),在篩選相關之總體經濟與社會經濟因素後,分析出影響臺北市住宅租金水準的自變數,再利用折現現金流量分析法,為投資型購屋者建構一套地上權住宅之合理價值評估模型。 本研究先蒐集崔媽媽基金會臺北市五個包含地上權住宅之行政區的住宅租金水準之歷史資料,以及政府統計資料中之總體經濟與社會經濟歷史資料,並將各行政分區的歷史期間(2001年至2010年)資料合併為Panel data,然後使用逐步多元迴歸方法來進行分析。經實證結果顯示,利用逐步多元迴歸分析所篩選出的變數(包括臺北市營造工程物價指數(CCI)與臺北市五個行政區平均每人可支配所得(IPj))對臺北市住宅租金水準的影響確實具有顯著影響,亦即CCI與IPj乃是台北市住宅租金水準的重要解釋變數。接下來,本研究利用政府1978至2010年所公布的九次臺北市歷史公告地價漲幅,將其調整為指數形式後進行簡單迴歸分析,發現時間t對公告地價指數(LI)具有顯著的影響。最後本研究利用上述三項變數進行某地上權個案的敏感度分析發現,臺北市五個行政區平均每人可支配所得(IPj)為影響當年淨現金流量(CF)的關鍵因素,是故,瞭解臺北市五個行政區平均每人可支配所得(IPj)的最好與最差變動程度,將可使投資者掌握地上權住宅投資的財務風險範圍。 經由本研究的實證研究,確認住宅租金水準(R)將會隨著屬於總體經濟變數的臺北市營造工程物價指數(CCI)及屬於社會經濟變數的臺北市五個行政區的平均每人可支配所得(IPj)的變動而變動。現今的估價實務,常將租金水準(R)簡化為常數或固定成長率的變數,造成估價標的所預測的現金流量價格往往會失真,且估價期間越長時,差距就會越大。 另一方面,本研究為找出各租金影響變數與時間t的關係是否為顯著,因此將屬於總體經濟變數的臺北市營造工程物價指數(CCI)共30年之數據,及將屬於社會經濟變數的臺北市五個行政區平均每人可支配所得(IPj)共10年數據,以臺北市平均每人可支配所得(IP)共29年的數據來取代,以之進行統計分析;實證發現時間t對(CCI)與(IP)的影響均為顯著,此意味著時間t的變動會影響臺北市的住宅租金水準,而租金收益為影響投資報酬率的關鍵因素,故在長期持有地上權住宅擬以出租獲利的情況下,時間變動的風險也是投資人不可忽視的。
From the viewpoint of house buyers and their financial returns, this study aims to apply the Discounted Cash Flow (DCF) Method of investment theory so as to evaluate the fair value of superficies right-based houses. By collecting the historical rental data of five administrative districts within Taipei City from Mother Tsui’s Foundation, to combine with the long-term historical macro-economical data of Taipei City and the short-term (2001-2010) social economical data of five administrative districts, the so-called Panel Data has been used. Then the multi-variable stepwise regression is employed. Results demonstrate that one macro-economical variable, i.e. Taipei City Construction Engineering Pricing Index or CCI, and another social economical variable of five administrative districts within Taipei City, i.e. the Disposable Income per capita or IPj, do have significant influence to house rent level of Taipei City. Then the historical (1978-2010) Public Released Land Value Inflation Rate of Taipei City, which has been released 9 times up to now, are used to conduct a simple regression analysis, by transforming the land value inflation rate into the index form, and then find out the time variable t will significantly influence the Public Released Land Value Index (LI). Finally a sensitivity analysis is conducted with the above-mentioned three independent variables to the influenced variable, i.e. house rent level of Taipei City, for a real world case of superficies right-based house in Taipei. Then the Disposable Income per capita or IPj of each administrative district is found to be the most sensitive variable to house rent level. That is to say, to focus on the Disposable Income per capita of each administrative district will make house buyers to be able to control their major investment risk. In conclusion, current practical real estate appraisal is often taking the house rent as a constant value or to change with a fixed growth rate for predigest, that will definitely produce bias in the predicted cash flow of the property, and the situation will get worse when the time frame of the superficies right period gets longer.